Anomaly detection in video with Bayesian nonparametrics

2016-06-27 · Olga Isupova, Danil Kuzin, Lyudmila Mihaylova

A novel dynamic Bayesian nonparametric topic model for anomaly detection in video is proposed in this paper. Batch and online Gibbs samplers are developed for inference. The paper introduces a new abnormality measure for decision making. The proposed method is evaluated on both synthetic and real data. The comparison with a non-dynamic model shows the superiority of the proposed dynamic one in terms of the classification performance for anomaly detection.

📄 PDF Abstract BibTeX arXiv:1606.08455

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Anomaly Detection Decision Making General Classification

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